A structured capability pathway aligned with ICH E6(R3), E8(R1), and Q9(R1), designed to help individuals and teams apply RBQM in real study environments.
Used by sponsor, CRO, and consulting teams to establish a shared RBQM foundation before and during implementation
Risk-Based Quality Management (RBQM) is an operating approach where risks to subject safety and data integrity are identified, assessed, and actively managed throughout the study lifecycle.
It builds on Quality by Design (QbD) principles (ICH E8(R1)), defining what matters most upfront and focusing oversight accordingly. This shifts teams from retrospective checks to continuous, risk-informed decision-making with clear rationale and traceability.
AI-supported tools can assist with data review and signal detection, provided their use remains controlled, understood, and aligned with GCP expectations.
ICH E6(R3) requires proportionate, risk-based oversight supported by ongoing evaluation and clear documentation.
Oversight must remain fit for purpose, traceable, and defensible, including when AI-supported tools are used. Accountability remains with qualified humans.
Clinical trial teams are moving toward more explicit risk-based oversight. What often slows adoption is not tooling, but uneven understanding across functions.
Increasing use of AI in trial processes adds pressure to ensure decisions remain controlled, explainable, and aligned with GCP.
Different interpretations of RBQM lead to:
The RBQM Essentials pathway helps organizations establish a shared foundation and progressively build role-relevant capability.
Teams need to:
The RBQM Essentials pathway builds these capabilities step-by-step.
A structured progression from foundational understanding to applied oversight and leadership.
Build a shared understanding of RBQM, QbD, CtQ, and risk-based oversight
→ Ideal for onboarding cross-functional teams
Translate RBQM principles into study-level design and risk evaluation
→ Focus on practical application using real scenarios
Enable end-to-end RBQM implementation and governance
→ For leaders responsible for oversight models and consistency
Apply AI in clinical trials with control and compliance
→ Supports capability needs under GCP and computerized systems
Apply RBQM to oversight planning and execution
Ensure proportionate, risk-based quality oversight
Interpret signals and support continuous review
Connect subject-level review with risk signals
Align cross-functional teams and decision-making
Shared Foundation Rollout
Train cross-functional teams on RBQM fundamentals
Role-Based Pathways
Align capability with function-specific responsibilities
Tailored iLT Programs
Adapt content to internal processes and study models
Supporting RBQM capability and implementation across global clinical organizations.
